Nanoboron nitride-filled heat-treated wood polymer nanocomposites: Comparison of different multicriteria decision-making models to predict optimum properties of the nanocomposites

2017 ◽  
Vol 51 (30) ◽  
pp. 4205-4218 ◽  
Author(s):  
Kadir Karakuş ◽  
Deniz Aydemir ◽  
Ahmet Öztel ◽  
Gokhan Gunduz ◽  
Fatih Mengeloglu
Keyword(s):  
Decision Making ◽  
Polymer Nanocomposites ◽  
High Density Polyethylene ◽  
Treated Wood ◽  
Multicriteria Decision Making ◽  
High Density ◽  
Multicriteria Decision ◽  
Wood Polymer ◽  
Heat Treated ◽  
Decision Making Models

The aim of this study is to investigate the effects of nanoboron nitride on the physical, mechanical, morphological and thermal properties of heat-treated wood high-density polyethylene composites. Three different multicriteria decision-making models such as the technique for order preference by similarity to ideal solutions, multi-attribute utility theory and compromise programming were used to predict the nanocomposites having optimum properties. High-density polyethylene as a matrix, heat-treated wood (30%) as a reinforcement filler and nanoboron nitride (0.5%, 1% and 2%) for improving the thermal stability were used; the composites prepared were grounded in a single-screw extruder, and the test samples were prepared with injection molding. According to the results, both testing and multicriteria decision-making models showed that heat-treated wood polymer nanocomposites with 2% nanoboron nitride have the optimum properties. Multicriteria decision-making methods are thought to be useful tools for materials having the optimal properties. It can be said that this study will be a guide for future material selection studies.

scholarly journals Approaches for multicriteria decision-making based on the hesitant fuzzy best–worst method

2021 ◽  
Author(s):  
Jian Li ◽  
Li-li Niu ◽  
Qiongxia Chen ◽  
Zhong-xing Wang
Keyword(s):  
Decision Making ◽  
Comparative Analysis ◽  
Programming Model ◽  
Multicriteria Decision Making ◽  
Decision Makers ◽  
Multicriteria Decision ◽  
Preference Relations ◽  
Fuzzy Preference Relations ◽  
Decision Making Models ◽  
Best Worst Method

AbstractHesitant fuzzy preference relations (HFPRs) have been widely applied in multicriteria decision-making (MCDM) for their ability to efficiently express hesitant information. To address the situation where HFPRs are necessary, this paper develops several decision-making models integrating HFPRs with the best worst method (BWM). First, consistency measures from the perspectives of additive/multiplicative consistent hesitant fuzzy best worst preference relations (HFBWPRs) are introduced. Second, several decision-making models are developed in view of the proposed additive/multiplicatively consistent HFBWPRs. The main characteristic of the constructed models is that they consider all the values included in the HFBWPRs and consider the same and different compromise limit constraints. Third, an absolute programming model is developed to obtain the decision-makers’ objective weights utilizing the information of optimal priority weight vectors and provides the calculation of decision-makers’ comprehensive weights. Finally, a framework of the MCDM procedure based on hesitant fuzzy BWM is introduced, and an illustrative example in conjunction with comparative analysis is provided to demonstrate the feasibility and efficiency of the proposed models.

scholarly journals Heat-Treated Wood Reinforced High Density Polyethylene Composites

2021 ◽  
Vol 72 (3) ◽  
pp. 219-229
Author(s):  
Kadir Karakuş ◽  
Deniz Aydemir ◽  
Gokhan Gunduz ◽  
Fatih Mengeloğlu
Keyword(s):  
Mechanical Properties ◽  
High Density Polyethylene ◽  
Wood Flour ◽  
Tensile Modulus ◽  
Treated Wood ◽  
High Density ◽  
Black Pine ◽  
Sem Images ◽  
Pine Wood ◽  
Heat Treated

This study investigated the effect of untreated and heat-treated ash and black pine wood flour concentrations on the selected properties of high density polyethylene (HDPE) composites. HDPE and wood flour were used as thermoplastic matrix and filler, respectively. The blends of HDPE and wood fl our were compounded using single screw extruder and test samples were prepared through injection molding. Mechanical properties like tensile strength (TS), tensile modulus (TM), elongation at break (EatB), fl exural strength (FS), fl exural modulus (FM) and impact strength (IS) of manufactured composites were determined. Wood fl our concentrations have significantly increased density, FS, TM and FM and hardness of composites while reducing TS, EatB and IS. Heat-treated ash and black pine fl our reinforced HDPE composites had higher mechanical properties than untreated ones. Composites showed two main decomposition peaks; one coming from ash wood flour (353-370 °C) and black pine wood fl our (373-376 °C), the second one from HDPE degradation (469-490 °C). SEM images showed improved dispersion of heat-treated ash and black pine wood flour. The obtained results showed that both the untreated and heat-treated ash/black pine wood flour have an important potential in the manufacture of HDPE composites.

scholarly journals Sustainability in the Business Sector: A Fuzzy Multicriteria Decision-Making Model for Financial Leasing Company Selection of the Vietnamese SMEs

SAGE Open ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 215824402110360
Author(s):  
Fengsheng Chien ◽  
Chia-Nan Wang ◽  
Ka Yin Chau ◽  
Van Thanh Nguyen ◽  
Viet Tinh Nguyen
Keyword(s):  
Decision Making ◽  
Interest Rates ◽  
Small And Medium Enterprises ◽  
Multicriteria Decision Making ◽  
Primary Concern ◽  
Multicriteria Decision ◽  
Financial Leasing ◽  
Criteria Weights ◽  
Leasing Company ◽  
Selection Of

The uses and management of capital is extremely important to the operation of any businesses. However, not all businesses have available capital, so the use of loans in many different forms is always an effective solution in managing corporate finance. Accompanying with businesses, many financial leasing companies have implemented products and programs to lend money to businesses with low interest rates. So, choosing the best financial leasing company is a primary concern of businesses. To increase competitiveness, financial leasing companies often offer preferential conditions to attract businesses. Choosing the best financial leasing service to leasing is important and necessary to those businesses. Thus, the selection of a financial leasing company by small and medium enterprises benefits from the application of Multicriteria Decision-Making (MCDM) methods which allows the decision maker to consider various qualitative and quantitative criteria. In this article, the author applied Fuzzy Analytical Network Process (FANP) to calculate the related criteria weights of the financial leasing company selection problem of businesses. Then, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is applied to rank the potential decision-making units. This research establishes one complete and efficient model for financial leasing company selection using FANP and TOPSIS methods. The proposed model is then applied into a real-world case study to demonstrate its feasibility.

Sign in / Sign up

Export Citation Format

Share Document